from __future__ import annotations


class Phase2SystemsMixin:
    def _initialize_cognitive_systems(self):
        """Initialize all cognitive systems for enhanced AI capabilities."""
        # Initialize each system independently to avoid cascading failures
        self.advanced_rag = None
        self.self_improvement = None
        self.feedback_learning = None
        self.performance_monitor = None

        # Advanced RAG System
        try:
            from ..cognitive.advanced_rag import AdvancedRAGSystem
            from ..core.vector_store import VectorStore
            vector_store = VectorStore(collection_name=f"toxo_rag_{self.domain}")
            self.advanced_rag = AdvancedRAGSystem(vector_store=vector_store, gemini_client=self.gemini_client, config=self.config)
            self.logger.info("Advanced RAG system initialized")
        except Exception as e:
            self.advanced_rag = None
            self.logger.warning(f"Advanced RAG not available: {e}")

        # Self-Improvement System
        try:
            from ..cognitive.self_improvement import SelfImprovementEngine
            self.self_improvement = SelfImprovementEngine(config=self.config)
            self.logger.info("Self-improvement engine initialized")
        except Exception as e:
            self.self_improvement = None
            self.logger.warning(f"Self-improvement engine not available: {e}")

        # Feedback Learning System
        try:
            from ..cognitive.advanced_feedback_learning import AdvancedFeedbackLearningSystem
            self.feedback_learning = AdvancedFeedbackLearningSystem(config=self.config)
            self.logger.info("Advanced feedback learning initialized")
        except Exception as e:
            self.feedback_learning = None
            self.logger.warning(f"Advanced feedback learning not available: {e}")

        # Performance Monitor
        try:
            from ..core.monitoring import PerformanceMonitor

            self.performance_monitor = PerformanceMonitor()
            self.logger.info("Performance monitor initialized")
        except Exception as e:
            self.performance_monitor = None
            self.logger.warning(f"Performance monitor not available: {e}")

    def _initialize_memory_systems(self):
        """Initialize all memory systems for comprehensive knowledge storage."""
        try:
            # Contextual Memory
            try:
                from ..memory.contextual_memory import ContextualMemorySystem

                self.contextual_memory = ContextualMemorySystem()
                self.logger.info("Contextual memory initialized")
            except ImportError:
                self.contextual_memory = None
                self.logger.warning("Contextual memory not available")

            # Episodic Memory
            try:
                from ..memory.episodic_memory import EpisodicMemorySystem

                self.episodic_memory = EpisodicMemorySystem()
                self.logger.info("Episodic memory initialized")
            except ImportError:
                self.episodic_memory = None
                self.logger.warning("Episodic memory not available")

            # Semantic Memory
            try:
                from ..memory.semantic_memory import SemanticMemoryEngine

                self.semantic_memory = SemanticMemoryEngine()
                self.logger.info("Semantic memory initialized")
            except ImportError:
                self.semantic_memory = None
                self.logger.warning("Semantic memory not available")

            # Working Memory
            try:
                from ..memory.working_memory import WorkingMemorySystem
                capacity = getattr(self.config.memory, "working_memory_capacity", 100) if hasattr(self.config, "memory") else 100
                self.working_memory = WorkingMemorySystem(capacity=capacity)
                self.logger.info("Working memory initialized")
            except ImportError:
                self.working_memory = None
                self.logger.warning("Working memory not available")

            # Long-term Memory
            try:
                from ..memory.long_term_memory import LongTermMemorySystem

                self.long_term_memory = LongTermMemorySystem()
                self.logger.info("Long-term memory initialized")
            except ImportError:
                self.long_term_memory = None
                self.logger.warning("Long-term memory not available")

            # Hierarchical Memory
            try:
                from ..core.hierarchical_memory import HierarchicalMemorySystem

                self.hierarchical_memory = HierarchicalMemorySystem(config=self.config)
                self.logger.info("Hierarchical memory system initialized")
            except ImportError:
                self.hierarchical_memory = None
                self.logger.warning("Hierarchical memory system not available")

        except Exception as e:
            self.logger.error(f"Failed to initialize memory systems: {e}")

    def _initialize_agent_framework(self):
        """Initialize multi-agent framework for collaborative AI."""
        try:
            # Agent Orchestrator
            try:
                from ..agents.orchestrator import AgentOrchestrator, CoordinationPattern

                self.orchestrator = AgentOrchestrator(config=self.config, coordination_pattern=CoordinationPattern.HIERARCHICAL)
                self.logger.info("Agent orchestrator initialized")
            except ImportError:
                self.orchestrator = None
                self.logger.warning("Agent orchestrator not available")

            # Specialized Agents
            agent_types = ["research", "creative", "analytical", "collaborative"]
            for agent_type in agent_types:
                try:
                    from ..agents.orchestrator import LLMAgent, AgentCapability

                    capabilities = [
                        AgentCapability(
                            name=f"{agent_type}_processing",
                            description=f"Specialized {agent_type} processing",
                            input_types=["text", "data"],
                            output_types=["text", "analysis"],
                            max_concurrent_tasks=2,
                            estimated_duration=10.0,
                        )
                    ]

                    agent = LLMAgent(
                        agent_id=f"{agent_type}_{self.domain}",
                        llm_client=self.gemini_client,  # Must support `.generate(...)`
                        capabilities=capabilities,
                        config={"domain": self.domain, "agent_type": agent_type},
                    )
                    setattr(self, f"{agent_type}_agent", agent)
                    self.logger.info(f"{agent_type.title()} agent initialized")
                except Exception as e:
                    setattr(self, f"{agent_type}_agent", None)
                    self.logger.warning(f"{agent_type.title()} agent not available: {e}")

            # Prefer orchestrator's internal messaging/router (single blessed framework).
            self.agent_communication = getattr(self.orchestrator, "message_router", None) if self.orchestrator else None

        except Exception as e:
            self.logger.error(f"Failed to initialize agent framework: {e}")

    def _initialize_processing_pipeline(self):
        """Initialize processing pipeline for multi-modal capabilities."""
        enable_local_processing_pipeline = (
            os.getenv("TOXO_ENABLE_LOCAL_PROCESSING_PIPELINE", "0") == "1"
            or bool(getattr(self.config, "enable_local_processing_pipeline", False))
        )
        if not enable_local_processing_pipeline:
            self.multimodal_processor = None
            self.document_processor = None
            self.advanced_document_processor = None
            return

        try:
            # Enhanced Multimodal Processor
            try:
                from ..processing.enhanced_multimodal_processor import EnhancedMultiModalProcessor

                self.multimodal_processor = EnhancedMultiModalProcessor(config=self.config)
                self.logger.info("Enhanced multimodal processor initialized")
            except ImportError:
                self.multimodal_processor = None
                self.logger.warning("Enhanced multimodal processor not available")

            # Document Processor
            try:
                from ..processing.document_processor import DocumentProcessor

                self.document_processor = DocumentProcessor(config=self.config)
                self.logger.info("Document processor initialized")
            except ImportError:
                self.document_processor = None
                self.logger.warning("Document processor not available")

            # Advanced Document Processor
            try:
                from ..processing.advanced_document_processor import AdvancedDocumentProcessor

                self.advanced_document_processor = AdvancedDocumentProcessor(gemini_client=self.gemini_client)
                self.logger.info("Advanced document processor initialized")
            except ImportError:
                self.advanced_document_processor = None
                self.logger.warning("Advanced document processor not available")

        except Exception as e:
            self.logger.error(f"Failed to initialize processing pipeline: {e}")

    def _initialize_enterprise_features(self):
        """Initialize enterprise-grade features for scalability."""
        try:
            # Load Balancer
            try:
                from ..core.load_balancer import LoadBalancer

                self.load_balancer = LoadBalancer()
                self.logger.info("Load balancer initialized")
            except ImportError:
                self.load_balancer = None
                self.logger.warning("Load balancer not available")

            # Cache Manager
            try:
                from ..core.caching import CacheManager

                self.cache_manager = CacheManager()
                self.logger.info("Cache manager initialized")
            except ImportError:
                self.cache_manager = None
                self.logger.warning("Cache manager not available")

            # Vector Store
            try:
                from ..core.vector_store import VectorStore

                self.vector_store = VectorStore(collection_name=f"toxo_{self.domain}")
                self.logger.info("Vector store initialized")
            except ImportError:
                self.vector_store = None
                self.logger.warning("Vector store not available")

            # Monitor
            try:
                from ..core.monitoring import ToxoMonitor

                self.monitor = ToxoMonitor()
                self.logger.info("Monitor initialized")
            except ImportError:
                self.monitor = None
                self.logger.warning("Monitor not available")

            # Advanced Analytics Manager
            try:
                from ..core.advanced_analytics import AdvancedAnalyticsManager

                self.analytics_manager = AdvancedAnalyticsManager(config=self.config)
                self.logger.info("Advanced analytics manager initialized")
            except ImportError:
                self.analytics_manager = None
                self.logger.warning("Advanced analytics manager not available")

        except Exception as e:
            self.logger.error(f"Failed to initialize enterprise features: {e}")

